Methods and systems for planning operations in manufacturing plants

ABSTRACT

A method and system for generating a production sequence for the resources of a manufacturing plant. This method comprises the steps of identifying the total amount of each product that the plant has to produce in one period of time, identifying the operation route and productivity for each product on each available resource, and identifying setup constraints. The method includes the further steps of identifying delivery dates already committed, and identifying the minimum and maximum stock levels for each resource. The identified factors are then used to generate a production sequence for each resource of the plant with a granularity of a defined time period.

This application is a continuation of copending application Ser. No.09/540,065, filed Mar. 31, 2000.

BACKGROUND OF THE INVENTION

This invention generally relates to planning systems for manufacturingplants. More specifically, the invention relates to intermediate termand shorter term planning, referred to as campaign planning and detailedplanning respectively, for manufacturing plants.

The Campaign Planning application defines the medium term productionplan, normally for three time periods (months), within the BusinessPlanning horizon, where the main objective is to minimize the cost ofequipment setup while creating a high level schedule (campaign plan) ofthe complete product mix sought by the Business Planning application ina cost effective manner.

The Detailed Planning application defines the short term production planwithin the campaign planning horizon based on actual customer orderswhere the main objective is to utilize the production capacity withinthe campaign plans for timely delivery of products to the customers. Itinteracts with other systems to ensure that customer orders are acceptedonly when they can be produced and delivered on time.

SUMMARY OF THE INVENTION

An object of this invention is to provide an improved campaign plan formanufacturing plants. Another object of the present invention is toprovide a campaign planning system to optimally allocate equipmentcapacity to expected orders in a multiple production line manufacturingplant.

A further object of this invention is to provide a detailed planningsystem to dynamically allocate orders to previously reserved productioncapacity for a manufacturing plant.

These and other objectives of the invention are attained with themethods and systems disclosed herein. In accordance with a first aspectof the invention, a method and system are provided for generating aproduction sequence for the resources of a manufacturing plant. Thismethod comprises the steps of identifying the total amount of eachproduct that the plant has to produce in one period of time, identifyingthe operation route and productivity for each product on each availableresource, and identifying setup constraints. The method includes thefurther steps of identifying delivery dates already committed, andidentifying the minimum and maximum stock levels for each resource. Theidentified factors are then used to generate a production sequence foreach resource of the plant with a granularity of a defined time period.

In accordance with a second aspect of this invention, a method andsystem are provided for planning operations of a manufacturing plant.The method comprises the steps of identifying equipment that can performa given step of an order route comprised of a sequence of steps, andevaluating the production time of the given step. A backward search isthen executed, starting at the last step of the route, to identify thefirst available time spot long enough to accommodate the given step.Preferably, the evaluating step includes the steps of identifying theproductivity and weight of the order, and evaluating the production timeon the basis of the productivity and weight of the order. Also,preferably the method includes the further step of checking throughinventory to determine if there is available material to perform thegiven step.

Further benefits and advantages of the invention will become apparentfrom a consideration of the following detailed description, given withreference to the accompanying drawings, which specify and show preferredembodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart illustrating a preferred campaign planning systemembodying this invention.

FIG. 2 is a flow chart showing a preferred detailed planning systemembodying the present invention.

FIGS. 3 and 4 show a computer system that may be used in the invention.

FIG. 5 illustrates a memory medium that can be used to hold a computerprogram for carrying out this invention.

FIG. 6 shows a functional architecture that may be used with the methodand system described herein.

FIG. 7 shows the functional architecture of the Year Planner.

FIG. 8 shows the functional architecture of the Master Planner of FIG.7.

FIG. 9 shows the functional architecture of the Detail Planner of FIG.8.

FIG. 10 shows a Production Scheduling system.

FIG. 11 shows the functional architecture of the Primary AreaScheduling.

FIG. 12 shows the functional architecture of the Finishing Area.

FIG. 13 shows the functional architecture of the Foundry Scheduling.

FIG. 14 shows the functional architecture of Dispatch Scheduling.

FIG. 15 shows the functional architecture of Order Specification andRouting.

FIG. 16 shows the functional architecture of Inventory Application.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the process of developing the campaign plans, relevant product mixrequirement, work-in-process inventory and orders already booked aretaken into consideration, so that the campaign plan generated isfeasible. Other constraints that are taken into account in each periodare equipment availability, purchased intermediate products, externalprocessing capacities, and material in stock by the beginning of theplanning cycle.

The Campaign Planning system generates a production sequence for eachresource of a steel mill plant with a granularity of a shift (8 hours).With reference to FIG. 1, the method takes into consideration the totalamount of each product that the plant has to produce in one period oftime (one month, for example), the operation route and productivity foreach product on each resource (type of equipment), several setupconstraints, the delivery dates already committed with clients along theperiod considered, and the minimum and the maximum stock levels for eachresource.

For that, this module runs an Integer Programming model with 1,000integer and 50,000 continuous variables in a risc platform under UNIXoperating system. The mathematical model is divided into two phases:Primary and Finishing Phases. The Finishing phase is divided intosub-models. One model for each finishing area (i.e., Stainless andSilicon areas). Given the input data for a period, each model isexecuted individually with their own constraints. The output of eachmodule is added up and synthesized as the input data for the otherphase, the Primary Area Phase. This phase has only one model and runsconsidering the constraints regarding the melt shop and Hot Strip Millareas. The output for all the model defines a Campaign Plan for a givenperiod (month).

The system is composed of a graphical user interface, an interface totransform graphical information in meaningful constraints for themathematical model, an optimization engine, and interfaces with othersystems, such as Business Planning, Detailed Planning, and Plant FloorOperations Systems.

The optimization engine core is based on IBM OSL library. Except by theGUI, everything else is located in a server that runs under UNIX.Communication with all other systems is made through message-passingtechnique using IBM MQSeries package and Oracle Database.

Through a Graphical User Interface (GUI), which shows the campaign planin a Gantt chart format, the user has the opportunity to make changes tothe generated plan and view the implications of the changes. Finally,once all the manual modifications are completed, the underlyingmathematical model is run again to validate that nothing has beenviolated due to the manual modifications.

A capacity feasible campaign plan, in effect, sets aside capacity to beused by the product groups for specified shifts. This plan is defined asthe amount of tonnage reserved for a given type of material by shift.The campaign plan also provides the necessary information for timely rawmaterials procurement.

In accordance with another aspect of the invention, a detailed planningsystem is provided to dynamically allocate orders to previously reservedproduction capacity for a manufacturing plant.

The process of creation of a detailed plan includes developing detailedproduction order process plans for every step of the routing provided bythe Order Dressing application. A detailed production order process planincludes the start and end dates for a given step in the route, thetonnage required, and the load on the resource in consideration. Theobjective of Detailed Planning is to develop a feasible plan within thebounds of the optimized campaign plan (created by the CampaignGeneration System).

During the order acceptance process, it ensures that the product mixgenerated by the Business Planning system is not violated. In such anevent, the user is warned. Before determining the tonnage required atany step (resource) in the route, and applicable material is utilizedand the load on the resource is placed only for the net amount. In doingso an order may have to be split if the total amount of the materials isnot found at a given process step.

With reference to FIG. 2, the method reads the options of feasiblepieces of equipment that can perform a given step of an order route andevaluates the production time of that step considering the appropriateproductivity and weight of the order. In order of preference for thefeasible pieces of equipment, it executes a backward search, starting atthe last step of the route, looking for the first available time spotlong enough to accommodate the step. All timing and precedenceconstraints are strictly considered. Also, before searching foravailability for a given route step, it first checks if there isavailable material through the Inventory Application system so that aminimum amount of capacity is consumed and the maximum of availablematerial is used.

The major advantages of this system is how capacity is optimized and theprecision that delivery dates are provided to an order. Despite of theprecision, the date is highly reliable, for the system considers a largenumber of constraints, which minimize discrepancy with reality.

The user can modify an order manually and replan it. The entire detailedplan can be replanned by the user at any time. Orders received back fromscheduling system are automatically replanned.

Detailed Planning uses a finite capacity planning of orders. Normally,backward planning is used to determine the latest date by which aprocess step is to be completed, if the desired delivery date must besatisfied. In specific situations, forward planning is used, forexample, when replanning of orders that could not be scheduled isperformed. Heuristics may be used to load batch annealing furnaces.

The system is composed by a graphical user interface with severalscreens, an evaluation engine, interface with multi-user graphicalinterfaces, physical data model, interface with Order Entry System,Order Dressing System, Campaign Generation System, Inventory ApplicationSystem and Scheduling System.

The evaluation engine is a server that continuously run under UNIX.Communication with all other systems is made through message-passingtechnique using IBM MQSeries package.

Various systems used in the present invention are described below.

As will be understood by those of ordinary skill in the art, the presentinvention may be carried out on any suitable computer or computernetwork. FIG. 3 illustrates, as an example, a computer of a type thatmay be used in the practice of this invention. Viewed externally in FIG.5, a computer system has a central processing unit 42 having disk drives44A and 44B. Disk drive indications 44A and 44B are merely symbolic of anumber of disk drives that might be accommodated by the computer system.Typically, these would include a floppy disk drive such as 44A, a harddisk drive (not shown externally) and a CD ROM drive indicated by slot44B. The number and type of drives vary, usually, with differentcomputer configurations. The computer has the display 46 upon whichinformation is displayed. A keyboard 50 and a mouse 52 are normally alsoavailable as input devices.

FIG. 4 shows a block diagram of the internal hardware of the computer ofFIG. 3. A bus 54 serves as the main information highway, interconnectingthe other components of the computer. CPU 56 is the central processingunit of the system, performing calculations and logic operationsrequired to execute programs. Read only memory 60 and random accessmemory 62 constitute the main memory of the computer. Disk controller 64interfaces one or more disk drives to the system bus 54. These diskdrives may be floppy disk drives, such as 66, internal or external harddrives, such as 70, or CD ROM or DVD (Digital Video Disks) drives, suchas 72. A display interface 74 interfaces a display 76 and permitsinformation from the bus to be viewed on the display. Communicationswith external devices can occur over communications port 78.

FIG. 5 shows a memory medium 80 that may be used to hold a computerprogram for implementing the present invention, and this medium may beused in any suitable way with any appropriate computer to carry out theinvention. Typically, memory media such as a floppy disk, or a CD ROM,or a Digital Video Disk will contain the program information forcontrolling the computer to enable the computer to perform its functionsin accordance with the invention.

Proposed Functional Architecture

FIG. 6 shows a functional architecture that may be used with the methodand system disclosed herein. The basic object of a functionalarchitecture is to establish a set of logical procedures that reflectthe operational behavior of an organization. The architecture of FIG. 6covers functional needs and offers some innovations in the operatingprocedures currently in use. Among these innovations, the number ofproduction planning and scheduling layers is reduced, whilstnevertheless increasing the level of detail of the activities to becarried out. Another significant innovatory aspect is the application ofthe open book concept for entering orders. Under this concept, as theorders are placed, they are allocated one by one to the plant'sresources. This means that planning can handle the plant's capacitysufficiently precisely to be able to set a reliable and speedy deliverydate for an order, whilst nevertheless retaining flexibility ofscheduling in order to best adapt the production sequence to inevitableunforeseen events. FIG. 6 shows the functional architecture. Theremainder of this text will explain in detail the other characteristicsand concepts supporting the raison d'être of this architecture.

The principal modules of the proposed architecture are:

Year Planner

Once a year, or whenever necessary, the production capacity of the plantis compared with the market conditions and an optimum proportion of howmuch is to be produced of each product is determined. The main eventswhich will occur in the plant, such as long periods of maintenance, areconsidered and handled so as to reduce their effects on the company'sprofit.

Master Planner

This module keeps a check on the production availability of each type ofproduct starting from a certain horizon (generally 3 months). Thisavailability is used to supply the order delivery date. The optimumproduct mix generated by the Year Plan is updated and used as a basicdatum by the Master Plan, which converts it from monthly periods toproduction weeks through the generation of production campaigns.Accordingly, the Master Planner can ensure that delivery datecommitments are made aggressively, but viably.

Detailed Planner

For orders placed a short time before the delivery date (generally lessthan three months), a meticulous analysis is made of the availability ofthe plant and inventory with the Detailed Planner module. Dailyproduction capacities are considered.

Primary and Finishing Area Scheduling

Orders must be selected and scheduled so as to meet commitments tocustomers and to effectively benefit from the plant's equipment.Grouping and sequencing constraints, configuration times andinter-dependence of equipment must be taken into consideration forloading the plant in the best possible way. As the production conditionschange, the plant's scheduling must be adjusted to meet the new contextand constraints.

Dispatch Area Scheduling

Shipping completes the processing stages of an order. The dispatch oforders must continue the process of optimization in the planning andscheduling undergone by the order, to minimize any delay in delivery andeffectively explore transport alternatives. The integration of Shippingwith Production Scheduling is achieved through the ability to view thematerial to be produced by the plant and by considering the loadrestrictions for dispatch.

Technical Specification and Routing of Orders

As the orders arrive, they must be specified technically and added tothe database from which production planning and scheduling extract theinformation relevant to them. The nomenclature and terminology specificto the user and its standard products must be supported by this module.

Inventory Application

This module matches up the material available in the plant with theorders to be produced. The material may be plates, partially processedcoils or finished products. Business rules are used to judge the qualityof the match, for defining which order will be used when more than onefits the material and for selecting which material will be allocated toan order when more than one material may be applied. An analysis of theimpact on plant capacity becomes necessary for each allocation.

Characteristics of the Proposed Functional Architecture

All the modules, such as Technical Specification and Routing of Orders,Planning, Production Scheduling and Inventory Application are fullyintegrated.

Both the “production for orders” and “production for stock” strategiescan be supported.

All the modules are highly flexible owing to the broad parametersettings of the data they use.

Constraints and requests that benefit customer satisfaction and themaximum productivity of the plant are also considered.

Uses advanced techniques of Combinatorial Optimization and ArtificialIntelligence, as well as algorithms specially designed for iron andsteel industry problems.

Year Planner

The main objectives of the Year Planner, shown in FIG. 7, are:

to identify the optimum mix of products to be produced for a certaintime horizon, given a market context and constraints to be met.

to analyse the impact of critical aspects, such as market segmentation,commitment of production between products and prioritization in servingcustomers.

creating a guide for the sales department with a view to the bestproduct mix for the company for the period in question.

Detailed by each type of product that the plant can produce, anobjective function is defined such that it can express the overallprofitability of the plant for any product mix. The best product mix isthat which maximizes this objective function, meeting all theconstraints imposed. This type of problem is generally resolved byLinear Programming models. The tool to be adopted for implementing themodel must provide, in addition to the solution, a sensitivity analysisof the constraints, identifying those that have the most impact onmaximizing the objective function.

The plan generated by this module is reviewed and, via a DecisionSupport System interface, the impact of various scenarios on theobjective function used can be tested. The final plan is published andstored for use as an initial platform for the lowest levels of planning.

FIG. 7 shows the functional architecture for the Year Planner.

Model Generator

This module is responsible for generating a suitable representation ofthe mathematical model defined by the user in the optimization module.The model consists of the objective function, which generally reflectsthe company's profit margin and the constraints to be imposed. Theconstraints usually consist of limits on the anticipated demand forproducts, capacity of the plant's machines and the relationship betweenprocesses. For the purpose of the Year Planner, the capacity of themachines may be just the number of hours that each of them is availablefor operation in a certain period of time.

Optimizer

This module generates the value of the objective function for the bestalternative of all the possibilities, i.e. it generates the optimumsolution. It also generates a sensitivity analysis enabling theidentification of which variables, parameters and constraints arecausing greater impact on the objective function.

Decision Support System

Via this system, the user interacts with the model, alters theparameters and constraints and observes the result and the impact of thechanges. This module ensures that the user will have the means ofimposing his decisions on any automatically generated solution.

Master Planner

The main objectives of the Master Planner, shown in FIG. 8, are:

1. To review the year planner assumptions and projections for the nextfew months and then confirm them or modify them.

2. To generate suitable campaign sequences for each month of production.

3. To analyse the following months in detail and generate a productionplan for the plant to be used in undertaking the date for orders to beplaced.

4. To allocate the orders to plant machines and generate viable deliverydates.

5. To generate information for the Planning of Supplies.

The Master Planner allocates the optimum quantities of products suppliedby the Year Plan to lesser periods, generally of one week or ten days induration. Accordingly, it must create the production campaign periodsfor the various types of products on the various plant equipment. Theoperating horizon of the Master Planner is usually three to six monthsfrom the current date, i.e. the horizon is dynamically adjusted eachmonth. This means that each month's production capacities can be revisedas long as the month is within the operating horizon.

New orders that fall within the operating horizon of the Master Plannerare allocated against the plant's weekly production capacities so thatthe order delivery date may be determined. The accounting of theremaining capacity is kept continually up to date to be used on thearrival of the next order. For orders exceeding one week's productioncapacity, the Master Planner performs a running total calculation of theweekly capacities prior to the date wanted by the customer and allocatesthe order to the number of weeks that are needed. If, even so, there isnot sufficient capacity for producing the order, it is not accepted. Theearliest date that the order can be produced is notified. In the eventof any cancellation of orders, the plant's available capacities areupdated. FIG. 8 shows the functional architecture for the MasterPlanner.

Generation of the Master Plan

The allocation of capacity to the machines specified by the Year Plan isconverted into weekly allocations, which form the basis of all theplanning of the Master and Detailed Planner. The master plans for eachproduct family are generated from non-detailed constraints of machinecapacity and forecasts of customer demands which may be introduceddirectly into the Master Planner or via the data originating from theYear Plan. Each generated plan supplies a capacity for each productfamily which can be feasibly produced by the plant.

Since changes and unexpected events are inevitable, the plans can berevised automatically, given the conditions for which the replanning isperformed, or manually, via the Decision Support System.

Campaign Generator

Once the Year Planner supplies the ideal product mix for the next fewmonths, this module analyses this mix and generates a sequence ofproduction campaigns that the various plant equipment must follow inorder to produce these products in an optimized manner. The generationand sequencing of these campaigns must be in accordance with the plant'sprocessing constraints and with the rules of business.

Allocation of Orders

When the orders are placed, they are assigned to periods of time,generally weeks, in which the master plans are created. Their deliverydates are determined and undertaken with the customer. If there is notsufficient capacity for producing in good time for the customer, thereason for this being impossible will be notified.

Reverse Planning

Starting from the requested delivery date, each stage of production inthe route of a product is examined and the consumption of capacity andexecution time are reflected in the Master Planner weekly periods.

Resource Allocation

Different products may require the same equipment in different ways.Thus, the allocation of equipment must be done in a balanced manner,just as the time in which the equipment is allocated to the product.Each product is associated with a load profile which gives how much theproduct consumes of each piece of equipment on its route in terms oftons per hour.

This module considers the periods in which the equipment may not beoperating, with the consequent repercussion on the available productioncapacity.

Available-for-Undertaking

The capacity not yet consumed for each week handled by the MasterPlanner is totalled and accounted week by week by this module. Thus, wehave the total available capacity at each period and for each productfamily. For each order that is accepted, the necessary capacity isdecremented from each item of equipment and reflected in theavailability of all the product families sharing the machines on theroute of each accepted product.

Decision Support System

This module enables the user to interact with the system forintroducing, observing and altering data and results supplied by theMaster Planner.

Detailed Planner

Even if an order has been entered normally by the Master Planner,nevertheless more thorough planning of the order is necessary when itsproduction period approaches. There are several reasons for this. Theorders currently in progress may consume a little more capacity thanexpected, reducing the capacity available for the entry of new orders.The plant's situation may have changed from the time that the orderswere entered. Customers may have requested changes in delivery dates orspecification of the previously requested orders. Material in productionhas been diverted and the order has to be replanned. Lack of sufficientraw material for processing the order.

Thus, the Detailed Planner, shown in FIG. 9, provides precise monitoringof capacity and replanning of orders, and also uses the availableinventory whenever possible. It forecasts the availability of the plantfor the orders already in progress and for those not yet begun. The mainobjectives of the Detailed Planner are:

1. To create detailed order plans by product family.

2. To keep an up-to-date and accurate accounting record of the capacityconsumed and available by product family and by equipment.

3. To generate a viable delivery date for new orders falling within theoperating horizon of the Detailed Plan.

4. To supply orders to the scheduling system for the requested period.

5. To use inventory availability for planning and replanning orders.

For better use of the plant's capacity, some orders may be broughtforward if there is excess capacity. Similarly, in the event ofoverload, some orders may be delayed and the user may then redefine theplant's available capacity for various product families in order toalleviate the impact of possible delays.

The functions of this module may be used to analyse the consequences ofexchanging, altering and replanning orders. Thus, the user can examinethe possibilities of speeding up the production of priority orders.

At each step in the production process, the detailed plans furnish theconsumption data for each type of material used in production. From thisdata, the appropriate amount of raw material can be calculated that willbe necessary to support production.

The final plans for each product family are published together with theproduction and inventory requirements. Replanned orders and unexpectedcapacity bottlenecks are reported.

The functional architecture of the Detailed Planner has the followingcharacteristics:

Production Order Planning

The planning mechanism loads the orders in progress and the new ordersstarting from the specified week for merging by the Master Planner andthose that have their delivery dates delayed will be listed for theuser. The production levels of each product line are defined for eachitem of equipment contained in their routes. This module tries toovercome bottlenecks by using alternative resources, starting orderprocessing earlier, or by delaying some orders. The orders each day, aswell as the initial and final inventory levels.

Reverse and Direct Planning

Starting from the delivery date, each stage of production in the orderroute must be examined to ensure sufficient time for producing theorder, given all the production times of each stage. If necessary, theorders can be projected from the week of merging for defining thenearest delivery date.

Equipment Load

This module is similar to that encountered in the Master Plan, but withmore details. It considers the time of processing by the equipment,equipment configuration time, line constraints and daily capacities.

Planning and Monitoring of Supplies and Power/Utility

The limiting constraints of supply and power are considered so as tomaintain a viable allocation of orders to the plant. Within the validlimits, the Detailed Planner reports the levels of supplies and powerthat will be necessary for producing orders.

Decision Support System

The user will have to interact with the Detailed Planner to resolveoperational exceptions and to assess alternatives for loading resourcesand replanning. With unforeseen events, it may be impossible to deliverall the orders without there being a delay; the user must intervene anddecide which will be delayed and which will not. The impacts of changesin quantity, specification and delivery date of orders also must beanalysed by the user.

Production Scheduling

The Production Scheduling system, shown in FIG. 10, is composed of fourmodules: Primary Area Scheduling, Finishing Area Scheduling, Dispatchand Foundry Area Scheduling. FIG. 10 shows these areas and therelationship between them.

Primary Area Scheduling

The architecture of the Primary Area Scheduling, shown in FIG. 11, isbased on the following requirements:

Providing a display of the primary area equipment for the desiredscheduling horizon, e.g. a week or several days (from here on we shallregard this horizon as being one week). The solution generated must takeinto consideration all significant constraints so that the scheduling isas faithful as possible to reality.

Generating a detailed schedule for the equipment, taking into accountpig iron supply constraints, constraints in grouping, sequencing andtiming of equipment and the supply demands of the Foundry and FinishingAreas.

The architecture of FIG. 11 provides an integrated schedule for all theprincipal equipment of the primary area.

The scheduling process begins with the selection of orders for aspecific week. Orders are grouped together for creating the best billetformation sequence from the point of view of the bar line and the beststand sequence from the point of view of the Hot Rolling Area. To thesesequences are added the pig iron supply constraints and the pig ironrequisitions made by the Foundry for then generating the scheduling ofwhat is actually viable to be produced by the steelworks. The actualschedules of ingots for the bar line, plates for the Hot Rolling area,limits of supply of pig iron by the Blast Furnaces and steel for theFoundry are considered for the final generation of billet and coilscheduling and for the internal scheduling of the Foundry. Thescheduling of the pig iron supply of the Blast Furnaces is generatedwithin the valid limits. Throughout this process, all the relevantconstraints will be considered for the maximum suitability of thesolution to the situation of the plant at any given moment.

Once a solution is generated, the user may erase and rework any part ofthe solution. Thus, any possible constraints which are not normallyrequired to be considered may be imposed manually by the user.

A new solution must be generated whenever the proposed schedulingclashes significantly with the plant situation. Examples of events thatmay require new scheduling are: diversion of material, insertion of neworders, order cancellations and breakdown of equipment.

The functional architecture modules of the Primary Area shown in FIG. 11are:

Preliminary Grouping of Billets

The bar finishing line orders are grouped according to the similarity ofcharacteristics wanted in the sequencing of the billets, e.g. grade ofsteel, delivery date and configuration of the bar rollers. Afterconsideration of the cold ingots available in stock, the best groupingof billets is generated. At this point, specific constraints of thesteelworks equipment should be disregarded.

Preliminary Sequencing of Billets and Ingots

Given the groupings supplied by the previous module, the best sequenceof billets is generated and the corresponding ingot sequence for the barrollers. One of the basic objectives is the hot charging of ingotswhenever possible. Available cold ingots are calculated. Steelworksconstraints are still disregarded.

Preliminary Grouping of Stands

All the orders requisitioned by Hot Rolling for the desired schedulinghorizon are grouped by the characteristics appropriate to the rollingprocess: e.g. width and thickness of the plates, delivery date, and typeof steel. Plates available in stock must be considered.

Preliminary Sequencing of Stands

Considering the stands formed in the previous module, a sequence ofstands is generated, so as to best meet the constraints of platerolling. Again, available cold plates are considered, but the majorityof the constraints relevant to the steelworks are not.

Formation of Runs and Continuous Ingoting and Blast Furnace Sequencing

For each ingot of the sequence requested by Bar Rolling and each plateof the sequence requested by Hot Rolling, the time is determined thatthe ingot or plate may wait between the end of ingoting and the start ofcharging for rolling. The ingots and plates are grouped in runs so as tomaximize the number of ingots or plates that overlap in the period thatthey have available to be charged hot. As the runs are formed, they areassigned to the equipment (e.g. BOFs, pot furnaces, degasifier) forensuring that the continuity of processing of the run within thesteelworks is viable. All the constraints of the continuous rolling millwhich may involve sequences of several runs are verified, as well as thelimitations and impositions of the Blast Furnaces. The demands from theFoundry are accommodated between the runs being created. This modulegenerates the possible scheduling of being supplied by the steelworksfor the ingots, plates, Foundry servicing and distribution and pig ironof the Blast Furnaces as near as possible to what is demanded at thesteelworks.

Allocation of Shaft Furnaces

Given the actual sequence of ingots to be produced by the steelworks,this module must select the cells of the shaft furnaces available andassign them the ingots, making all the necessary time allowances, aswell as considering the reheating of the available cold ingots.

Sequencing of the Bar Rollers

Once the sequence is given with which the ingots are available to theshaft furnaces, the sequence with which they must be rolled isdetermined, taking into account the timing and configuration constraintsof the rollers.

Final Grouping of Stands

Given the final sequence of plates to be produced by the steelworks, thetime available for hot rolling each of them is calculated. By maximizingthe number of plates with overlapping of these times, the plates aregrouped in stands, achieving homogeneity in width, thickness, deliverydate and type of steel of the plates. The available cold plates are alsoconsidered. All the constraints of forming the stands must be satisfied.

Final Sequencing of Stands

Once the stands are defined, the constraints imposed by the hot rollingarea and the nearest order delivery date within each stand areconsidered, generating the final scheduling of the stands andconsequently of the hot coils and rough plates.

Decision Support System

The user may review the solutions generated and alter them. If themodifications violate any constraint, the user will be notified, but itis his decision whether or not to keep the modification.

Finishing Area Scheduling

FIG. 12 shows the functional architecture of a finishing area. Thefinishing area shown in this Figure consists of the Stainless Steel Coiland Plate Finishing Lines, the Silicon Finishing Line, their respectiveCutting Lines, the Carbon Cutting Line and the Bar Rolling Mill.

The proposed architecture for the Finishing Area is based on thefollowing points:

generation of a schedule for the Finishing Area equipment for a certainhorizon (e.g. a week), taking into account all the constraints of thisequipment.

minimizing the configuration times of the equipment and order delays.

The orders supplied by the Primary Area are grouped together andsequenced for a week. All maintenance periods must be taken intoaccount. Inventory Application has an important role in the use ofmaterial in progress which is diverted.

A description follows of the approaches to be used for scheduling eachof the finishing lines.

Stainless and Silicon Steel Lines

These two finishing lines have very similar characteristics with regardto the operating procedures of production: all the equipment in theselines, as a rule, passes through two operating stages. The first is agrouping of orders meeting the operating constraints of the equipment,e.g. all the coils in a group must belong to the same type of steel. Thesecond stage is that of sequencing, in which the coils of a group aresequenced, e.g. the coils must be in order of decreasing length. At theend of a sequencing stage, the coils are released to the next equipmenton their route, being made available to be processed.

The sets of coils that are grouped together in a particular machine andhave the same route are still not allocated to one order, but to a setof orders, i.e. the allocation of metal units to orders is done as lateas possible, so as to benefit from the possibility of selecting whichorder should be treated as diverted and which should continue forwardwhen a diversion occurs. At the start of each system operation, thefunction of refining order allocation creates the initial groups oforders for each of the items of equipment.

The grouping, sequencing and order allocation refinement cycle isrepeated until all the orders have been processed by all the equipmenton their routes. The Decision Support System enables the observation ofthe results and the intervention of the user at all levels of decisiontaken (i.e. valid for the remaining lines of the Finishing Area).

Bar Rolling

The scheduling of billets (rough bars) originating from the rollers(MILL 1 and 2) is taken into account so that suitable groups of materialare formed and sequenced by the equipment of the Bar Line FinishingArea. The approach to the solution of this type of problem may beregarded as a special case of the approach described forStainless/Silicon steel, since the equipment has similar grouping andsequencing characteristics. Both the scheduling of billets and that offinished products can be altered and adjusted by the Decision SupportSystem.

Foundry

FIG. 13 shows the functional architecture of the Foundry Scheduling.This is an area that operates separately from the rest of the plant,except for requisitions for steel from the Steelworks and pig iron fromthe Blast Furnaces.

The first step in the process of casting is the allocation of humanresources to the planning phase of a new order, in which the models andproduction routes are generated for the equipment. External models mayalso be acquired and their routes determined.

Owing to the existence of more equipment than manpower to operate it,human resources become critical in the Foundry. Accordingly, a carefulcheck is made to simultaneously allocate a human resource to an item ofequipment so as to carry out each task specified in the routing of anorder.

The final production phase of an order may involve a finishing stage,when we then have the scheduling of the finished products. Again, boththe data supplied to the Foundry and that generated by it may bemodified by the user via the Decision Support System.

Dispatch Scheduling

FIG. 14 shows a functional architecture of Dispatch Scheduling. Thetransport function completes the production process of an order in theplant. This function must generate a schedule that minimizes delay indelivery and suitably explores transport alternatives. The architectureof FIG. 14 is based on the following basic points:

Generating a schedule for a week (or any desired period) for each meansof transport (lorry, train, ship, etc.) taking into account thescheduling of the finished products produced by the plant.

Adjusting the daily scheduling whenever necessary.

Developing a load schedule based on the haulage companies' scheduling.

Generating new scheduling when any serious distortion occurs in theavailability of products or of the means of transport.

Generating a schedule that minimizes delivery delay and transport cost.

Enabling monitoring of the performance of the haulage companies.

Shipment Grouping

This function receives the scheduling of the finished products andgroups them together with those found in a shipping depot. These groupswill be dispatched by the various haulage companies. This moduleminimizes delivery delay and the cost of transport.

Load Sequencing

The grouped orders are sequenced to form a load schedule based on thehaulage companies' scheduling. Constraints such as availability of spacefor handling the load and haulage capacity must be taken into account.

Decision Support System

The user must have a clear view of the orders that are to arrive fromthe plant and of those in the shipping depots. Moreover, the user mustbe able to correct and alter any data considered or generated by theDispatch Scheduling module. This function also monitors the level ofdeviation between what is scheduled and what is carried out, generatingthe necessary information for when new scheduling is wanted.

Technical Specification and Routing of Orders

On entering an order, it must be quickly and dynamically specified. Theorder specification and routing architecture of FIG. 15 (FIG. 10) isbased on the following points:

Reducing or eliminating manual specification and routing through themaintenance and updating of metallurgical knowledge and specification oforders.

Dynamically specifying orders with routing information, as soon as theorders are placed by the customers.

Keeping the orders in a repository equally accessible by Planning andScheduling.

Providing a viability check for the specification of orders andautomatically re-routing the orders whenever necessary.

The order specification process begins with access to the customerorders supplied by the order entry function. Customer requests aretranslated into the user's internal nomenclature.

According to the type of product specified, the grade of steel, thewidth, the length and the quality, the routing is generated to reflectthe load demands of the order on the equipment of the route. The routingmust include information on the sequence of equipment on which the orderneeds to be processed, processing times on each item of equipment,production rates, and intermediate dimensions at each stage.

The viability of producing the order as specified is checked against thecapacities of the equipment to ensure that the order can be physicallyprocessed as specified. If the check fails, an alternative route, if itexists, must be automatically generated.

All the orders specified are evaluated with cost information based ontheir route. These orders are equally accessible by Planning andScheduling.

Specification of Orders

This function translates the information from the customer order to theuser's internal order standard. International technical standards areused and pre-defined information is supplied in cases where somecharacteristics of the order are not provided by the customer.

Checking the Validity of the Order

This function is performed for each order placed. If the order cannot beprocessed, this information is passed on to the Decision Support Systemfunction, which must provide the means for requests to be altered ifpossible.

Route Generation

Once an order passes the production viability check, its standardproduction route must be generated. Information on the order, customerpreference and rolling mill conditions are taken into account.

Alternative Route Generation

If a route cannot be found, a request for re-routing must be sent tothis function which, in its turn, will attempt to discover analternative route.

Cost Generation

This function calculates the cost of an order based on the routingassociated with it.

Decision Support System

The user can observe the information supplied and generated by theSpecification and Routing module and modify it as he considersnecessary.

Inventory Application

The Inventory application process, shown in FIG. 16, matches therelevant attributes of the available material to the specifications ofthe orders and determines the eligibility of the material for a givenorder. The material may be plates, partially finished coils or finishedproducts. Business rules are used to judge the suitability of theallocation between the available material and the order, both when thereare several materials for one order and when there are several possibleorders for a particular material. Inventory Application to an order willcause an impact upon the Detailed Planner and Scheduling.

The Inventory Application process begins with the analysis of new ordersto determine which can be assigned to the existing inventory of platesand coils. Some characteristics that may be considered are: chemicalproperties, quality, width, thickness and weight.

When multiple candidates are available, the best choice is identifiedaccording to a predefined preference list. Once a plate or coil has beenapplied to an order, it will no longer be available for otherapplications. The user may intervene whenever necessary.

Allocation/Re-allocation of Orders

Order data and inventory data are processed by this function. Specificattributes of orders, plates and coils can be compared. The matchingcriteria, order attributes and the candidate plates or coils areexamined. The viability of the match between the order and the materialis determined.

Predefined rules are used for prioritizing in the event of multiplematching possibilities.

Decision Support System

This function has to support the intervention of the user in thedecision process on the suitability and availability of candidatematerial to be allocated to an order.

Benefits

The described functional architecture will bring a series of benefits.Some of them are found below:

Optimization of the profit margin and resources of the company from theYear Planner to the plant's Production Scheduling.

Weighted balance between market demands and the plant's productionpotential.

Rapid and precise response to viability of meeting customer requests.

The expected date of delivery will be determined promptly, taking intoaccount all the intermediate stages of production. Inventory informationwill be taken into account in the arrival of new orders and in thereallocation of diverted orders.

The automation of the Planning and Scheduling Systems will enable usersto concentrate on tasks which are more critical and strategic to thecompany.

The Production Scheduling of the whole plant will be fully integrated,from the Steelworks to the end of the Finishing Lines.

Planning will automatically generate the formation and sequencing ofcampaigns.

The Specification and Routing System will be sufficiently intelligent torelease people from tedious manual processes. The specification processwill consider standard and alternative routes.

Application of material will be considered on entering orders. Theprocess will be automatic and performed in real time. All the relevantaspects of matching orders with available materials will be considered.

The total time between the placing of the order and its being shipped tothe customer will be reduced.

Planning and Scheduling will be continually adapted to the plant'sconditions in order to exploit its capacities to the maximum and betterservice the market.

While it is apparent that the invention herein disclosed is wellcalculated to fulfill the objects stated above, it will be appreciatedthat numerous modifications and embodiments may be devised by thoseskilled in the art, and it is intended that the appended claims coverall such modifications and embodiments as fall within the true spiritand scope of the present invention.

What is claimed is:
 1. A method for generating a production sequence for the resources of a manufacturing plant, comprising the steps: (A) identifying the total amount of each product that the plant has to produce in one period of time including both already received orders and expected future orders for said one period of time; (B) identifying the operation route and productivity for each product on each available resource; (C) identifying setup constraints; (D) identifying delivery dates already committed; (E) identifying the minimum and maximum stock limits for each resource; (F) using the factors identified in steps (a) through (e) to generate a production sequence for each resource of the plant with a granularity of a defined time period.
 2. A method according to claim 1, wherein step (f) includes the step of allocating equipment capacity to expected orders.
 3. A method according to claim 1, wherein step (F) includes the step of splitting said amount of each product that the plant has to produce in said one period of time, over two subperiods of said one period of time.
 4. A method according to claim 1, further comprising the steps of: (G) manufacturing the products in accordance with the productions sequences; and (H) waiting for resources to be available before planning for a product.
 5. A method according to claim 1, wherein said one period of time is at least one month.
 6. A method according to claim 5, wherein said defined time period is 8 hours.
 7. A system for generating a production sequence for the resources of a manufacturing plant, comprising: (A) means for identifying the total amount of each product that the plant has to produce in one period of time including both already received orders and expected future orders for said one period of time; (B) means for identifying the operation route and productivity for each product on each available resource; (C) means for identifying setup constraints; (D) means for identifying delivery dates already committed; (E) means for identifying the minimum and maximum stock limits for each resource; (F) means for using the factors identified elements (a) through (e) to generate a production sequence for each resource of the plant with a granularity of a defined time period.
 8. A method according to claim 1, wherein the using means includes means for allocating equipment capacity to expected orders.
 9. A system according to claim 7, wherein the means for using the identified factors to generate a production sequence includes means for splitting said amount of each product that the plant has to produce in said one period of time, over two subperiods of said one period of time.
 10. A system according to claim 7, further comprising (G) means for manufacturing the products in accordance with the productions sequences, and wherein the means for using the identified factors to generate the production sequence waits for resources to be available before planning for a product.
 11. A system according to claim 7, wherein said one period of time is at least one month.
 12. A system according to claim 11, wherein said defined time period is 8 hours.
 13. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for generating a production sequence for the resources of a manufacturing plant, the method comprising the steps: (A) identifying the total amount of each product that the plant has to produce in one period of time including both already received orders and expected future orders for said one period of time; (B) identifying the operation route and productivity for each product on each available resource; (C) identifying setup constraints; (D) identifying delivery dates already committed; (E) identifying the minimum and maximum stock limits for each resource; and (F) using the factors identified in steps (a) through (e) to generate a production sequence for each resource of the plant with a granularity of a defined time period.
 14. A program storage device according to claim 13, wherein step (f) includes the step of allocating equipment capacity to expected orders.
 15. A program storage device according to claim 13, wherein step (E) includes the step of splitting said amount of each product that the plant has to produce in said one period of time, over two subperiods of said one period of time.
 16. A program storage device according to claim 13, wherein said method steps further comprise: (G) manufacturing the products in accordance with the productions sequences; and (H) waiting for resources to be available before planning for a product.
 17. A program storage device according to claim 13, wherein said one period of time is at least one month.
 18. A program storage device according to claim 17, wherein said defined time period is 8 hours. 